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dc.contributor.authorTeng, Yui-Chiehen_US
dc.contributor.authorWang, Jun-Zheen_US
dc.contributor.authorHuang, Jiun-Longen_US
dc.date.accessioned2015-07-21T11:21:53Z-
dc.date.available2015-07-21T11:21:53Z-
dc.date.issued2014-01-01en_US
dc.identifier.isbn978-3-319-13186-3; 978-3-319-13185-6en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-319-13186-3_12en_US
dc.identifier.urihttp://hdl.handle.net/11536/125145-
dc.description.abstractGiven a project requiring a set of skills, the team formation problem in social networks aims to find a team that can cover all the required skills and has the minimal communication cost. Previous studies considered the team formation problem with a leader and proposed efficient algorithms to address the problem. However, for large projects, a single leader is not capable of managing a team with a large number of team members. Thus, a number of leaders would be formed and organized into a hierarchy where each leader is responsible for only a limited number of team members. In this paper, we propose the team formation problem with the communication load constraint in social networks. The communication load constraint limits the number of team members a leader communicates with. To solve the problem, we design a two-phase framework. Based on the proposed framework, we first propose algorithm Opt to find an optimal team, under the communication load constraint, with minimal communication cost. For large social networks, we also propose algorithm Approx to find a nearly-optimal team. Experimental results show that algorithm Opt is able to find optimal teams and is more efficient than the brute-force algorithm. In addition, when nearly-optimal teams are acceptable, algorithm Approx is much more scalable than algorithm Opt for large social networks.en_US
dc.language.isoen_USen_US
dc.subjectTeam formationen_US
dc.subjectDegree-constrained minimum spanning treeen_US
dc.subjectSocial networken_US
dc.titleTeam Formation with the Communication Load Constraint in Social Networksen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1007/978-3-319-13186-3_12en_US
dc.identifier.journalTRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MININGen_US
dc.citation.volume8643en_US
dc.citation.spage125en_US
dc.citation.epage136en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000354705300012en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper


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